Planning stability in a product recovery system

Recovery of used products is an issue of growing importance due to customer expectations and environmental regulation. As a consequence, companies need to adapt their material management taking into account inbound flows of used products. Corresponding inventory control models have been proposed in literature. In this paper we address the issue of planning stability in a product recovery context. To this end, we consider rolling horizon planning for a stock point facing stochastic demand and product returns. We analyze the impact of the return flow on planning stability and compare the system behaviour with a traditional production environment. We show that structural results derived for traditional inventory models remain valid in a product recovery context. Moreover we discuss counterintuitive effects resulting from interaction between planning stability and stock levels.     

Quantitative evaluation of product disassembly for recycling

This paper presents a method for evaluating the ease-of-disassembly of products. Its primary use is in designing products for recycling, but it also facilitates consideration of servicing and maintenance, and making environmentally-related decisions. The method is developed and discussed in the context of relatively small products that can be disassembled by a seated person using hand-held tools. The evaluation procedure is centered around a spreadsheet-like chart and uses a catalog of task difficulty scores. The scores were derived from work-measurement analyses of standard disassembly tasks, and provide a means of identifying weaknesses in the design and comparing alternatives quantitatively. The structure of the evaluation chart and the derivation of difficulty scores are explained, followed by a demonstration of analyzing a computer central processing unit. The limitations of the method and future extensions are outlined.     

Configuration analysis to support product redesign for end-of-life disassembly

End-of-life product disassembly is an important process that makes the parts of a product available for different material and part recycling processes at end of its useful life. However, the efficiency of the disassembly process greatly affects the economics of meeting the environmental goals set for the product. An important determinant of the efficiency of disassembly is the product configuration. Therefore, it is essential for the designer to assess these implications of the configuration while designing a product for end-of-life disassembly. In this paper, a formal model, called the Configuration-Value (CV) model, is proposed to evaluate and analyse the effect of configuration on disassembly. The model focuses on the rate of value extraction during the disassembly process. The model is used to identify the critical bottlenecks in the configuration, to help the designer to identify the design changes that need to be made to improve the product 'disassemblability'. An example is presented to demonstrate the application of the proposed model.     

An approach for estimating the end-of-life product disassembly effort and cost

Disassembly is the process of physically separating a product into its parts or subassembly pieces. The overall economics of the disassembly process, and in particular the cost to disassemble, is still not well understood. In this paper our goal is to introduce a methodology that will support and facilitate the economic analysis of the disassembly activity. We present a multi-factor model to compute the disassembly effort index (DEI) score, which is representative of the total operating cost to disassemble a product. The DEI score can then be compared against the projected market value of the disassembled parts and subassemblies to get an economic measure. To develop the DEI model we surveyed a variety of commercial disassembly facilities. Based on these surveys we propose a multifactor weighted estimation scheme. The seven factors are (i) time, (ii) tools, (iii) fixture, (iv) access, (v) instruct, (vi) hazard, and (vii) force requirements. The DEI scale is defined in the 0 to 100 range. This range is assigned on a weighted basis to each of the seven factors. For each factor, an independent utility scale is formulated, using the assigned range as anchors. Using a conversion scale the DEI score is used to derive an estimate of disassembly cost and the disassembly return on investment. An example is presented.     

Interactive AR-assisted product disassembly sequence planning (ARDIS)

This paper presents a proof-of-concept novel near real-time interactive AR-assisted product disassembly sequence planning system (ARDIS) based on product information, such as interference matrix and 3D models. The system is developed using Unity and consists of three modules, including an intelligent disassembly sequence planning module, an automatic content authoring module and an intuitive augmented reality (AR) user interface (UI) with various features, such as a virtual panel for customisation and an option panel for sequence regeneration. Given the retrieval targets specified by a user, optimised disassembly sequences are computed using an evolutionary computing algorithm. For the sequences computed, the respective AR disassembly instruction sequences, such as 2D text instructions and animated 3D models, are generated dynamically based on a taxonomy that links each disassembly step in a sequence with the corresponding Unity templates that have been created beforehand. Hence, the need for manual authoring to provide AR disassembly guidance is reduced. If necessary, the user can request for alternative disassembly sequences which can be re-computed in near real-time. Several case studies have been carried out to demonstrate and evaluate the performance of the system within the laboratory environment.     

Digital tools for material selection in product design

The increasing number of normalized materials, promoters and users led to a significant amount and diversity of databases and software for material selection, presenting differentiating abilities for the materials selection process.     

Disassembly line in product recovery

There are several situations in a product recovery environment where products may be disassembled for economical and regulatory reasons. The disassembly line is perhaps the most suitable setting for disassembly of large products (consisting of numerous components) as well as small products received in large quantities. This paper discusses the importance of a disassembly line in product recovery. The objective of the disassembly line is to utilize the available resources as efficiently as possible while meeting the demand for recovered parts. However, there are many complicating matters that need to be considered to create an efficient disassembly line. Our primary goal is to discuss these issues and provide a better understanding of the complications and their effects on the disassembly line. We also demonstrate how some important factors in disassembly can be accommodated to balance a paced disassembly line by modifying the existing concept of assembly line balancing. An example is presented to illustrate the approach.     

Evaluation model and algorithm of product disassembly process with stochastic feature

Disassembly planning is considered as the optimization of disassembly sequences with the target of the shortest disassembly time, the lowest disassembly cost, and the minimum disassembly energy consumption. However, obsolete products suffer from the influence of a variety of uncertainties, the disassembly process of products has the strong uncertain feature. Traditionally, to account for this uncertainty, each removal operation or removal task is assumed to be an activity or event with certain probability, and the determination of the optimal path of a disassembly process is merely a probabilistic planning problem based on this assumption. In this article, based on the established stochastic disassembly network graph, combined with different disassembly decision-making criterion, typical stochastic models for disassembly time analysis are developed. In addition, a two-phase approach is proposed to solve the typical stochastic models. Initially, according to different removal probability density functions, disassembly probability density functions of feasible disassembly paths are determined by a time-domain method or frequency-domain method, and additionally, after the disassembly probability density functions have been obtained, the quantitative evaluation of a product disassembly process and stochastic optimization of feasible disassembly paths are realized by a numerical solution method. Finally, a numerical example is illustrated to test the proposed concepts and the effectiveness of the proposed approach.     

The value of information systems for product recovery management

This article sheds light on the role of information systems in product recovery management. We first develop analytical models and then provide a numerical example to determine under what conditions investments in Information-intensive Product Recovery Systems (IPRS) are economically justifiable for manufacturers and when policy-makers need to consider facilitating their implementation. The results of the analytical models indicate that the recovery network (collection) structure and product characteristics determine if precision improvements or increased sorting speed associated with IS investments will lead to higher profit gains. Manufacturers should carefully assess conflicting impacts of current manufacturing and recycling technology trends on the value of IPRS. Implementing IPRS might end up reducing manufacturers' profits under a highly time efficient decentralised collection structure. We show that negotiations with competitors about IPRS implementation may lead to a win–win situation and allow consumers to enjoy the lowest product price if the binding force of the agreement is strong. Otherwise, some manufacturers follow free-rider strategies. This article has immediate application to manufacturers' IS strategy and to government policy-makers considering investing in and/or structuring product recovery closed-loop supply chain processes within their jurisdictions. It also opens a potential stream of research concerning the role of IPRS to automate, informate and transform closed-loop supply chains for eco-efficiency.     

Analysis of a product recovery system

The continuous growth in consumer waste in recent years has seriously threatened the environment. Environmentally conscious manufacturing and product recovery has become an obligation to the environment and to society. Many countries are contemplating regulations that force manufacturers to take back used products from consumers so that the components and materials retrieved from the products may be reused and/or recycled. We focus on a product recovery system in a remanufacturing system. Product recovery aims to minimize the amount of waste sent to landfills by recovering materials and parts from old or outdated products by means of recycling and remanufacturing. It should be considered when designing and managing the manufacturing systems. We propose a new analytical approach to evaluating the product recovery system with stochastic variability. This model applies the traditional inventory theory to the production/inventory management with consideration for disposal and return. The system is formulated by a discrete time Markov chain. It is composed of the states denoted by the number of the inventory, the transition probabilities between states and the costs associated with the transitions. Using the Markov analysis, we can calculate the total expected average cost per period exactly. Numerical examples are given to show the property of the management system and optimize the product recovery system.     

Strategies for evaluating performance of flexibility in product recovery system

In view of the increasing business opportunities with changing customer attitudes and stricter legislations, the handling of returns has become a daunting challenge. The need for decision models for evaluating return performance has been observed in the academia and the corporate world. To improve return system performance, integrated flexible reverse enterprise systems have attracted attention from researchers as well as practitioners. This paper addresses these critical issues and proposes a novel integrated and Flexible recovery system decision model. The proposed model aims to facilitate enterprises in assessing their product recovery system capability, and in improving overall performance. The proposed model is a natural extension of several well-grounded policies for conventional reverse supply chains and can be verified on a simulation platform.     

A Petri Net based approach to determine the disassembly strategy of a product

In order to protect the environment and regain value added to products, a process known as disassembly has come into the limelight. This process is to be applied to reuse abandoned goods and materials. Manufacturers are being forced to establish disassembly plants and to develop their products' designs so as to maintain the government's dictate to dispose off their products in an environmentally responsible manner. This research presents a cost-based heuristic analysis for a circuit board assembly. Various components of the product and their assembly relationships are represented by a Petri Net diagram. Firing the transitions of the disassembly Petri Net is integrated with cost-based indices to develop an effective disassembly strategy. The methodology discussed here simplifies the decisionmaking process involved in disassembly planning. A comprehensive disassembly process planning system is proposed here and is exemplified by a case study of circuit board assembly.     

Analysis of flexible decision strategies for sustainability-focused green product recovery system

Identifying and analysing key decision variables that an organisation can opt for in order to initiate resource recovery from return activities and improve overall performance is a challenge. Therefore, to assist organisations which are involved in or about to initiate an effective recovery process, this paper provides guidelines to establish flexible decision strategies using the interpretive structural modelling (ISM) approach. This study has identified interrelationships between green variables such as supplier commitment, cost, regulations, etc. and has categorised relevant enablers. Further, variables such as capacity utilisation, customer satisfaction, energy consumption reduction, etc. are recognised as outcomes or results. After statistically verifying these variables, it has been inferred that driving enablers aid in promoting performance variables, while the result variables represent outcomes achieved via the driving variables. Further, using MICMAC analysis, a graphical categorisation of the variables is done on the basis of the impact on performance. Later prioritisation of variables having high driving power and low dependence is conducted. Inputs in the proposed model are taken through a case study conducted in the paper industry. The proposed model can be quite helpful and can act as a generic tool to achieve the desired performance improvement of green product recovery systems.     

An improved co-evolutionary algorithm for green manufacturing by integration of recovery option selection and disassembly planning for end-of-life products

There is a strong need for recovery decision-making for end-of-life (EOL) products to satisfy sustainable manufacturing requirements. This paper develops and tests a profit maximisation model by simultaneously integrating recovery option selection and disassembly planning. The proposed model considers the quality of EOL components. This paper utilises an integrated method of multi-target reverse recursion and partial topological sorting to generate a feasible EOL solution that also reduces the complexity of genetic constraints handling. In order to determine recovery options, disassembly level and disassembly sequence simultaneously, this paper develops an improved co-evolutionary algorithm (ICA) to search for an optimal EOL solution. The proposed algorithm adopts the evolutionary mechanism of localised interaction and endosymbiotic competition. Further, an advanced local search operator is introduced to improve convergence performance, and a global disturbance strategy is also suggested to prevent premature convergence. Finally, this paper conducts a series of computational experiments under various scenarios to validate the meta-heuristic integrated decision-making model proposed and the superiority of the developed ICA. The results show that the proposed approach offers a strong and flexible decision support tool for intelligent recovery management in a ubiquitous information environment. We discuss the theoretical and practical contributions of this paper and implications for future research.     

形式追随材料--材料在产品设计中的应用

提出了一种新颖的产品特征结构,该结构能清晰地表达了产品设计中产品的个性与材料、加工工艺以及易用性的关系,特别讨论了构成产品个性的3个层次的内容.然后以具体案例为例,阐述了如何针对产品个性的各个方面,恰当地运用材料及其加工工艺来创建产品的个性特征.     

A sorption-filtration material for recovery of radioactive iodine from gaseous aerosol exhausts

The efficiency of radioactive iodine recovery was studied as influenced by the type of filtration material and sorbent (OU-A carbon), sorbent surface density, and type and concentration of impregnating agent (AgNO₃, TEA, KI, BaI₂, etc.). A regression equation adequately describing the correlation dependence of ¹³¹I break through the sorption-filtration material on the sorbent surface density (OU-A carbon, 50–200 g m^–2) and impregnating agent concentration (AgNO₃ and TEA, 1–25 wt %) was obtained. The dynamic capacity of impregnated OU-A carbon for molecular iodine was determined; it varies from 170 to 350 mg g^–1. Based on these experimental results, a heat-resistant sorption-filtration material (Filosorb-D) for recovery of radioactive iodine was developed; this material consists of one or two layers of filtration material (FPA, PP-PE) containing imbedded impregnated OU-A carbon (100–500 g m^–2) and one layer of FSB-75-11 or MVFE-22 filtration material to remove aerosols. The operation properties of the Filosorb-D sorption-filtration material are as follows: filtration velocity up to 6 cm s^–1, aerodynamic resistance 480 Pa, efficiency of radioactive iodine recovery 99.0–99.9%, operation life 10 000–15 000 h, and desorption of radioactive iodine and sorbent carry-away < 1–2%.Translated from Radiokhimiya, Vol. 46, No. 6, 2004, pp. 559–563.Original Russian Text Copyright © 2004 by Kornienko, Ampelogova, Krupennikova.     

Simple optimal replenishment and disposal policies for a product recovery system with leadtimes

The paper addresses a problem of product recovery management where a single product is stocked in order to fulfill a stochastic demand of customers who may return products after usage, thus generating also stochastic product returns. The material flow can be controlled by procuring new products on the one hand, and by remanufacturing or disposal of returned items on the other. A situation is considered where all costs are proportional and where remanufacturing as well as procurement needs a fixed deterministic leadtime which can be different for both activities. For periodic review control it is shown how the optimal decision rules for procurement, remanufacturing and disposal can be evaluated by exploiting the functional equations of a dynamic programming formulation. The serious impact of leadtimes on the complexity of the control rule is elaborated, and it is demonstrated for which leadtime situations simple optimal policies can be derived.     

Joint decision-making on automated disassembly system scheme selection and recovery route assignment using multi-objective meta-heuristic algorithm

Green treatment on Waste Electrical and Electronic Equipmenthas increasingly attracted attention due to its significant environmental benefits and potential recovery earnings. Automated disassembly has been regarded as a powerful solution to enable more efficient recovery operations. Although numerous studies have contributed to the issues of disassembly, there are few researches that focus on decision model for selecting disassembly system scheme and recovery route in automated disassembly. In this paper, we propose a two-phase joint decision-making model to address this problem with the goal of balancing disassembly profit with environmental impact. First, we establish a multi-objective optimisation model to obtain the Pareto optimal recovery routes for each automated disassembly system scheme. Both recovery profit and energy consumption are evaluated for multi-station disassembly system. We design a multi-objective hybrid particle swarm optimisation algorithm based on symbiotic evolutionary mechanism to solve the proposed model. Then, we compare the Pareto optimal solutions of all the system schemes using a fuzzy set method and identify the best scheme. Finally, we conduct real case studies on the automated disassembly of different waste electric metres. The results demonstrate the superiority of automated disassembly and validate the effectiveness of our proposed model and algorithm.